A postdoctoral position is now available at Johns Hopkins iMIND (Director: Dr. Akira Sawa). We seek a talented and highly motivated bioinformatician or computational biologist to study the functions and dysfunctions of the brain using multimodal data. We welcome experienced data scientist with achievements in neuroscience as well as other fields such as genetics, cancer, and immunology.

Johns Hopkins iMIND is a multidisciplinary coalition of clinicians, basic science researchers, and data scientists from different departments, with activities directly connected to several clinical centers, such as the Johns Hopkins Schizophrenia Center. The mission of our coalition is to conduct basic and translational research to understand brain functions and disorders, to educate the next generation of undergraduates, graduate students, residents, postdoctoral fellows, and early career researchers, and ultimately to provide the finest possible clinical care for individuals with brain disorders. Fitting with the concept of “precision medicine”, we wish to establish a novel, multi-disciplinary entity of biomedical science.

There are many exciting ongoing projects at iMIND. One of these projects that the successful candidate will immediately join is first episode psychosis (FEP) project. This project brings clinicians, basic science researchers, and data scientists together to study pathophysiological mechanisms of psychosis at multiple levels and to propose possible interventions for the condition with a very high social burden.
Psychosis is a disturbance of brain function at the intersection of cognition, emotion, and perception, associated with impaired social function. Thus, in addition to its implication in clinical neuroscience, we can address fundamental questions in basic neuroscience through this human study.

For long-term research goal, a successful candidate will develop computational methods/analysis pipelines to answer the following questions
• How to take advantage of multimodal datasets (molecular profiles, brain imaging data, and clinical observations) to stratify patients and then discover biomarkers and drug targets?
• How to utilize longitudinal data to stratify patients and then discover biomarkers and drug targets in the disease trajectory?
• How to utilize public datasets and take advantage of our membership in the genomic consortia of brain disorders?

Qualifications (Education, Experience and Skills)
• A Ph.D. in computer science, applied math, neuroscience, or related field
• Experience in using cutting-edge computational methods to analyze next generation sequencing data, metabolomic data, proteomics data, brain imaging data, or clinical data, supported by strong publications
• Good knowledge of statistics and proficient in R or Python
• Ability to work collaboratively with members from different research backgrounds
• Experience in metadata analysis is a plus
• Experience in machine learning is a plus